Introduction: Social Network Analysis - A primer for sport scientists.

Relational data in sports

@Waesche2017 offer a typology of possible networks in sports. Their article is also an amazing resource to start your journey into SNA (in sports and beyond).

Types of networks in sports based on Waesche et al. (2017)

Network.type	Description
Competition Networks	Results of games, rankings or structural patterns in sport (e.g. two-mode networks such as athletes at same competitions, players in same team). Relative performance or structural patterns are analyzed.
Interaction Networks (intra-event)	Relations are rule-based elements of the game (e.g. passes), often analyzed for effectiveness.
Inter-organizational Networks	Network structures between organizations (e.g. collaboration between sport providers, franchises, clubs, event organizers).
Intra-organizational Networks	Network structures within organizations (e.g. communication among team members or within sport associations).
Affiliation Networks	Affiliations of social actors with aggregations of social actors (e.g. membership of individuals in organizations, participation of actors at events). Data are usually collected as two-mode networks.
Social Environments	Representation of a sport-related social environment as a network in which individual sports actors (e.g. athletes, individuals, teams) are embedded. Analysis of support, influence etc.

Network phenomena: Global and individual levels

We can broadly distinguish between network measures on the individual and global level. Individual level metrics tell us something about a member of the network. How many integrated is he/ she? How central? What role does he/ she play? Global metrics tell us something about the overall structure of the network. How centralized is it? How well connected? How many parts are there?

Networks as independent variables

What is the influence of structure?

Example: English soccer teams

@Grund2012 examine the relationship between the passing structure of English soccer teams (network characteristics on the global level as an independent variable) on team success.

Example: something with individual-level dependent variable

Networks as dependent variables

How does structure come about?

Example:

@Gyarmati2014 study different styles of soccer teams, again using passing data. This is maybe not an exact case of a network being the dependent variable, as they mostly seem to be interested in description. However, you could think about how these networks come about. Does it depend on the ligue? The age of the coach? The nationality of the players?…

Setting boundaries

Nominalist and realist [@Waesche2017]

Conclusion: A checklist to inform your research design

• Am I studying a relational phenomenon? What are my ties/ links?
• What is the content of my ties?
• Do I look at network phenomena at the global or individual level?
• Are network phenomena my dependent or independent variable?
• How would I go about setting boundaries for my network?